A valuable feature of Intel Advisor is its Roofline Analysis Chart, which provides an intuitive and powerful visualization of actual performance measured against hardware-imposed performance ceilings. Intel Advisor’s vector parallelism optimization analysis and memory-versus-compute roofline analysis, working together, offer a powerful tool for visualizing an application’s complete current and potential performance profile on a given platform.

This year, OpenMP*, the widely used API for shared memory parallelism supported in many C/C++ and Fortran compilers, turns 20. OpenMP is a great example of how hardware and software vendors, researchers, and academia, volunteering to work together, can successfully design a specification that benefits the entire developer community.

Game developers face a unique challenge – how to make their graphics-heavy applications perform well across a very wide spectrum of hardware devices, not just high-end systems. So while an early version of a game might have been developed on some high-end system with 10 teraflops of CPU potential in a discrete graphics card, how do you scale it down to smaller consumer devices where optimization options are more limited?

OpenMP is a good example of how hardware and software vendors, researchers, and academia, volunteering to work together, can successfully design a standard that benefits the entire developer community. Today, most software vendors track OpenMP advances closely and have implemented the latest API features in their compilers and tools. With OpenMP, application portability is assured across the latest multicore systems, including Intel Xeon Phi processors.

Parallel STL now makes it possible to transform existing sequential C++ code to take advantage of the threading and vectorization capabilities of modern hardware architectures. It does this by extending the C++ Standard Template Library with an execution policy argument that specifies the degree of threading and vectorization for each algorithm used.

Intel Advisor, an integral part of Intel Parallel Studio XE 2017, can help identify portions of code that could be good candidates for parallelization (both vectorization and threading). It can also help determine when it might not be appropriate to parallelize a section of code, depending on the platform, processor, and configuration it’s running on. Intel Advisor Roofline Analysis reveals the gap between an application’s performance and its expected performance.

Discovering where the performance bottlenecks are and knowing what to do about it can be a mysterious and complex art, needing some very sophisticated performance analysis tools for success. That’s where Intel® VTune™ Amplifier XE 2017, part of Intel Parallel Studio XE, comes in.

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